Facile Route for Fabrication of Ferrimagnetic Mn3O4 Spinel Material for Supercapacitors with Enhanced Capacitance
Bibliographic record
Abstract
The purpose of this investigation was the development of a new colloidal route for the fabrication of Mn3O4 electrodes for supercapacitors with enhanced charge storage performance. Mn3O4-carbon nanotube electrodes were fabricated with record-high capacitances of 6.67 F cm−2 obtained from cyclic voltammetry tests at a scan rate of 2 mV s−1 and 7.55 F cm−2 obtained from the galvanostatic charge–discharge tests at a current density of 3 mA cm−2 in 0.5 M Na2SO4 electrolyte in a potential window of 0.9 V. The approach involves the use of murexide as a capping agent for the synthesis of Mn3O4 and a co-dispersant for Mn3O4 and carbon nanotubes. Good electrochemical performance of the electrode material was achieved at a high active mass loading of 40 mg cm−2 and was linked to a reduced agglomeration of Mn3O4 nanoparticles and efficient co-dispersion of Mn3O4 with carbon nanotubes. The mechanisms of murexide adsorption on Mn3O4 and carbon nanotube are discussed. With the proposed method, the time-consuming electrode activation procedure for Mn3O4 electrodes can be avoided. The approach developed in this investigation paves the way for the fabrication of advanced cathodes for asymmetric supercapacitors and multifunctional devices, combining capacitive, magnetic, and other functional properties.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".